Network-Wide Packet Capture and Analytics Hosting

EndaceFabric

EndaceFabric enables multiple EndaceProbe™ Analytics Platforms to be connected into a network-wide fabric that is centrally searchable and provides visibility into, and accurate recording of, network traffic across an entire network– including visibility into high-speed 40Gbps and 100Gbps links. The distributed fabric is centrally managed using the EndaceCMS Central Management Server™ which reduces OPEX and CAPEX.

The architecture of the EndaceFabric enables huge scalability. EndaceProbes can be stacked and grouped to provide lossless recording of traffic on links running at 100Gbps and beyond with massive packet storage capacity sufficient to store weeks or months of recorded network traffic.

EndaceProbes can also be synchronized with a common, accurate time source - such as a GPS time source - to ensure packet time-stamping retains its nanosecond-level accuracy across complex, highly distributed networks. This precision makes it possible to reconstruct network events accurately even on distributed networks.

Read more about EndaceFabric scalability in our Distributing and Stacking EndaceProbes with EndaceFabric solution brief.

InvestigationManager

InvestigationManager™ is a virtual machine application that lets analysts conduct network-wide investigations and searches across an entire EndaceFabric, or a group of EndaceProbes, to quickly find the packets they need.

At the heart of InvestigationManager is EndaceVisionTM, a browser-based investigation tool that lets analysts select data sources from multiple EndaceProbes and analyze recorded traffic from all these sources simultaneously.

Due to the distributed, parallel nature of the EndaceFabric architecture, searches can be conducted across a hundred EndaceProbes, and petabytes of data, incredibly quickly, dramatically improving analyst performance.

Customers can deploy as many instances of InvestigationManager as they need to support simultaneous data mining and facilitate investigations for multiple concurrent users.